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This book explores various applications of deep learning to the
diagnosis of cancer,while also outlining the future face of deep
learning-assisted cancer diagnostics. As is commonly known,
artificial intelligence has paved the way for countless new
solutions in the field of medicine. In this context, deep learning
is a recent and remarkable sub-field, which can effectively cope
with huge amounts of data and deliver more accurate results. As a
vital research area, medical diagnosis is among those in which deep
learning-oriented solutions are often employed. Accordingly, the
objective of this book is to highlight recent advanced applications
of deep learning for diagnosing different types of cancer. The
target audience includes scientists, experts, MSc and PhD students,
postdocs, and anyone interested in the subjects discussed. The book
can be used as a reference work to support courses on artificial
intelligence, medical and biomedicaleducation.
This book explores various applications of deep learning-oriented
diagnosis leading to decision support, while also outlining the
future face of medical decision support systems. Artificial
intelligence has now become a ubiquitous aspect of modern life, and
especially machine learning enjoysgreat popularity, since it offers
techniques that are capable of learning from samples to solve newly
encountered cases. Today, a recent form of machine learning, deep
learning, is being widely used with large, complex quantities of
data, because today's problems require detailed analyses of more
data. This is critical, especially in fields such as medicine.
Accordingly, the objective of this book is to provide the
essentials of and highlight recent applications of deep learning
architectures for medical decision support systems. The target
audience includes scientists, experts, MSc and PhD students,
postdocs, and any readers interested in the subjectsdiscussed. The
book canbe used as a reference work to support courses on
artificial intelligence, machine/deep learning, medical and
biomedicaleducation.
This book explores various applications of deep learning to the
diagnosis of cancer,while also outlining the future face of deep
learning-assisted cancer diagnostics. As is commonly known,
artificial intelligence has paved the way for countless new
solutions in the field of medicine. In this context, deep learning
is a recent and remarkable sub-field, which can effectively cope
with huge amounts of data and deliver more accurate results. As a
vital research area, medical diagnosis is among those in which deep
learning-oriented solutions are often employed. Accordingly, the
objective of this book is to highlight recent advanced applications
of deep learning for diagnosing different types of cancer. The
target audience includes scientists, experts, MSc and PhD students,
postdocs, and anyone interested in the subjects discussed. The book
can be used as a reference work to support courses on artificial
intelligence, medical and biomedicaleducation.
This book explores various applications of deep learning-oriented
diagnosis leading to decision support, while also outlining the
future face of medical decision support systems. Artificial
intelligence has now become a ubiquitous aspect of modern life, and
especially machine learning enjoysgreat popularity, since it offers
techniques that are capable of learning from samples to solve newly
encountered cases. Today, a recent form of machine learning, deep
learning, is being widely used with large, complex quantities of
data, because today's problems require detailed analyses of more
data. This is critical, especially in fields such as medicine.
Accordingly, the objective of this book is to provide the
essentials of and highlight recent applications of deep learning
architectures for medical decision support systems. The target
audience includes scientists, experts, MSc and PhD students,
postdocs, and any readers interested in the subjectsdiscussed. The
book canbe used as a reference work to support courses on
artificial intelligence, machine/deep learning, medical and
biomedicaleducation.
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